Silent Suffering: A Study on the Abuse and Neglect of Elderly in the District of Kolkata, West Bengal.

  • Published In: Indian Journal of Health & Wellbeing, 2025, v. 16, n. 3. P. 593 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Sarkar, Aditi; Bandyopadhyay, Barnika 3 of 3

Abstract

This study investigates the prevalence, nature, and impact of abuse and neglect experienced by elderly individuals in the District of Kolkata, West Bengal. Employing an exploratory sequential mixed methods design, the research first conducted qualitative interviews to explore lived experiences, which informed the development of a structured survey instrument. A total of 100 elderly individuals (50 males & 50 females) aged 60 and above were selected using random sampling. Findings reveal that 68% of respondents had experienced some form of abuse, with emotional abuse (51%) and verbal abuse (73%) being the most common. Financial exploitation and neglect were also significantly reported. Family members emerged as the primary perpetrators in 67% of the cases. Emotional neglect, lack of medical care, and financial dependency were prominent issues. Alarmingly, 62% of respondents were unaware of their legal rights, and 43% felt unsafe in their living environments. The study highlights the silent yet pervasive suffering of elderly individuals and underscores the urgent need for targeted community interventions, awareness programs, and policy implementation to safeguard the rights and well-being of senior citizens. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Indian Journal of Health & Wellbeing. 2025/09, Vol. 16, Issue 3, p593
  • Document Type:Article
  • Subject Area:Health and Medicine
  • Publication Date:2025
  • ISSN:2229-5356
  • Accession Number:188772331
  • Copyright Statement:Copyright of Indian Journal of Health & Wellbeing is the property of Indian Association of Health, Research & Welfare and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.